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MCQOPTIONS
This section includes 124 Mcqs, each offering curated multiple-choice questions to sharpen your Computer Science Engineering (CSE) knowledge and support exam preparation. Choose a topic below to get started.
| 51. |
Feature of ANN in which ANN creates its own organization or representation of information it receives during learning time is |
| A. | adaptive learning |
| B. | self organization |
| C. | what-if analysis |
| D. | supervised learning |
| Answer» C. what-if analysis | |
| 52. |
There are also other operators, more linguistic in nature, called that can be applied to fuzzy set theory. |
| A. | hedges |
| B. | lingual variable |
| C. | fuzz variable |
| D. | none of the mentioned |
| Answer» B. lingual variable | |
| 53. |
A fuzzy set has a membership function whose membership values are strictly monotonically increasing or strictly monotonically decreasing or strictly monotonically increasing than strictly monotonically decreasing with increasing values for elements in the universe |
| A. | convex fuzzy set |
| B. | concave fuzzy set |
| C. | non concave fuzzy set |
| D. | non convex fuzzy set |
| Answer» B. concave fuzzy set | |
| 54. |
decides who becomes parents and how many children the parents have. |
| A. | parent combination |
| B. | parent selection |
| C. | parent mutation |
| D. | parent replace |
| Answer» C. parent mutation | |
| 55. |
Basic elements of EA are ? |
| A. | parent selection methods |
| B. | survival selection methods |
| C. | both a and b |
| D. | noneof these |
| Answer» D. noneof these | |
| 56. |
Applying recombination and mutation leads to a set of new candidates, called as ? |
| A. | sub parents |
| B. | parents |
| C. | offsprings |
| D. | grand child |
| Answer» D. grand child | |
| 57. |
Fitness function should be |
| A. | maximum |
| B. | minimum |
| C. | intermediate |
| D. | noneof these |
| Answer» C. intermediate | |
| 58. |
Parameters that affect GA |
| A. | initial population |
| B. | selection process |
| C. | fitness function |
| D. | all of these |
| Answer» E. | |
| 59. |
EV is considered as? |
| A. | adaptive |
| B. | complex |
| C. | both a and b |
| D. | noneof these |
| Answer» D. noneof these | |
| 60. |
EV is dominantly used for solving . |
| A. | optimization proble |
| B. | mnp problem |
| C. | simple problems |
| D. | noneof these |
| Answer» B. mnp problem | |
| 61. |
GBML stands for |
| A. | genese based machi |
| B. | genes based mob |
| C. | genetic bsed machi |
| D. | noneof these |
| Answer» D. noneof these | |
| 62. |
LCS stands for |
| A. | learning classes syste |
| B. | learning classifier |
| C. | learned class syste |
| D. | mnoneof these |
| Answer» C. learned class syste | |
| 63. |
EC stands for? |
| A. | evolutionary comput |
| B. | evolutionary com |
| C. | electronic computa |
| D. | noneof these |
| Answer» B. evolutionary com | |
| 64. |
GA stands for |
| A. | genetic algorithm |
| B. | genetic asssuranc |
| C. | genese alforithm |
| D. | noneof these |
| Answer» B. genetic asssuranc | |
| 65. |
Discrete events and agent-based models are usuallly used for . |
| A. | middle or low level o |
| B. | high level of abstr |
| C. | very high level of ab |
| D. | none of these |
| Answer» B. high level of abstr | |
| 66. |
doesnot usually allow decision makers to see how a solution to a en |
| A. | simulation ,complex |
| B. | simulation,easy p |
| C. | genetics,complex p |
| D. | genetics,easy problem |
| Answer» B. simulation,easy p | |
| 67. |
Determining the duration of the simulation occurs before the model is validated and te |
| A. | true |
| B. | false |
| Answer» C. | |
| 68. |
cannot easily be transferred from one problem domain to another |
| A. | optimal solution |
| B. | analytical solution |
| C. | simulation solutuon |
| D. | none of these |
| Answer» D. none of these | |
| 69. |
What are different types of crossover |
| A. | discrete and interme |
| B. | discrete and conti |
| C. | continuous and inte |
| D. | none of these |
| Answer» B. discrete and conti | |
| 70. |
What is the first step in Evolutionary algorithm |
| A. | termination |
| B. | selection |
| C. | recombination |
| D. | initialization |
| Answer» E. | |
| 71. |
Elements of ES are/is |
| A. | parent population siz |
| B. | survival populatio |
| C. | both a and b |
| D. | none of these |
| Answer» D. none of these | |
| 72. |
in ES survival is |
| A. | indeterministic |
| B. | deterministic |
| C. | both a and b |
| D. | none of these |
| Answer» E. | |
| 73. |
Evolution Strategies typically uses |
| A. | real-valued vector re |
| B. | vector representa |
| C. | time based represe |
| D. | none of these |
| Answer» B. vector representa | |
| 74. |
Evolution Strategies is developed with |
| A. | selection |
| B. | mutation |
| C. | a population of size |
| D. | all of these |
| Answer» E. | |
| 75. |
what are the parameters that affect GA are/is |
| A. | selection process |
| B. | initial population |
| C. | both a and b |
| D. | none of these |
| Answer» D. none of these | |
| 76. |
Evolutionary programming was developef by |
| A. | fredrik |
| B. | fodgel |
| C. | frank |
| D. | flin |
| Answer» C. frank | |
| 77. |
Chromosomes are actually ? |
| A. | line representation |
| B. | string representa |
| C. | circular representat |
| D. | all of these |
| Answer» C. circular representat | |
| 78. |
Idea of genetic algorithm came from |
| A. | machines |
| B. | birds |
| C. | aco |
| D. | genetics |
| Answer» E. | |
| 79. |
Evolutionary algorithms are a based approach |
| A. | heuristic |
| B. | metaheuristic |
| C. | both a and b |
| D. | noneof these |
| Answer» B. metaheuristic | |
| 80. |
Survival is approach. |
| A. | deteministic |
| B. | non deterministic |
| C. | semi deterministic |
| D. | noneof these |
| Answer» B. non deterministic | |
| 81. |
recombination is applied on candidates. |
| A. | one |
| B. | two |
| C. | more than two |
| D. | noneof these |
| Answer» C. more than two | |
| 82. |
LCS belongs to based methods? |
| A. | rule based learning |
| B. | genetic learning |
| C. | both a and b |
| D. | noneof these |
| Answer» B. genetic learning | |
| 83. |
mutation is applied on candidates. |
| A. | one |
| B. | two |
| C. | more than two |
| D. | noneof these |
| Answer» B. two | |
| 84. |
Genetic algorithms are example of |
| A. | heuristic |
| B. | evolutionary algo |
| C. | aco |
| D. | pso |
| Answer» C. aco | |
| 85. |
which of the following is a sequence of steps taken in designning a fuzy logic machine |
| A. | fuzzification->rule ev |
| B. | deffuzification->r |
| C. | rule evaluation->fuz |
| D. | rule evaluation->defuz |
| Answer» B. deffuzification->r | |
| 86. |
All of the follwing are suitable problem for genetic algorithm EXCEPT |
| A. | pattern recognization |
| B. | simulation of biol |
| C. | simple optimization |
| D. | dynamic process contr |
| Answer» D. dynamic process contr | |
| 87. |
Tabu search is an example of ? |
| A. | heuristic |
| B. | evolutionary algo |
| C. | aco |
| D. | pso |
| Answer» B. evolutionary algo | |
| 88. |
can a crisp set be a fuzzy set? |
| A. | no |
| B. | yes |
| C. | depends |
| D. | all of the above |
| Answer» C. depends | |
| 89. |
Fuzzy logic deals with which of the following |
| A. | fuzzy set |
| B. | fuzzy algebra |
| C. | both a and b |
| D. | none of the above |
| Answer» D. none of the above | |
| 90. |
What denotes the core(A) in a fuzzy set? |
| A. | {x|ua(x)>0} |
| B. | {x|ua(x)=1} |
| C. | {x|ua(x)>=0.5} |
| D. | {x|ua(x)>0.8} |
| Answer» C. {x|ua(x)>=0.5} | |
| 91. |
What denotes the support(A) in a fuzzy set? |
| A. | {x|ua(x)>0} |
| B. | {x|ua(x)<0} |
| C. | {x|ua(x)<=0} |
| D. | {x|ua(x)<0.5} |
| Answer» B. {x|ua(x)<0} | |
| 92. |
A={1/a,0.3/b,0.2/c,0.8/d,0/e} B={0.6/a,0.9/b,0.1/c,0.3/d,0.2/e} What will be the inte |
| A. | {0.6/a,0.3/b,0.1/c,0.3 |
| B. | {0.6/a,0.8/b,0.1/c |
| C. | {0.6/a,0.3/b,0.1/c,0 |
| D. | {0.6/a,0.3/b,0.2/c,0.3/ |
| Answer» B. {0.6/a,0.8/b,0.1/c | |
| 93. |
A={1/a,0.3/b,0.2/c,0.8/d,0/e} B={0.6/a,0.9/b,0.1/c,0.3/d,0.2/e} What will be the co |
| A. | m{0/a,0.7/b,0.8/c,0.2/ |
| B. | {0/a,0.9/b,0.7/c,0 |
| C. | {0.8/a,0.7/b,0.8/c,0 |
| D. | {0/a,0.7/b,0.8/c,0.9/d, |
| Answer» B. {0/a,0.9/b,0.7/c,0 | |
| 94. |
A={1/a,0.3/b,0.2/c,0.8/d,0/e} B={0.6/a,0.9/b,0.1/c,0.3/d,0.2/e} What will be the uni |
| A. | {1/a,0.9/b,0.1/c,0.5/ |
| B. | {0.8/a,0.9/b,0.2/c |
| C. | {1/a,0.9/b,0.2/c,0.8 |
| D. | {1/a,0.9/b,0.2/c,0.8/d, |
| Answer» D. {1/a,0.9/b,0.2/c,0.8/d, | |
| 95. |
The bandwidth(A) in a fuzzy set is given by |
| A. | (a)=|x1*x2| |
| B. | (a)=|x1+x2| |
| C. | (a)=|x1-x2| |
| D. | (a)=|x1/x2| |
| Answer» D. (a)=|x1/x2| | |
| 96. |
The intersection of two fuzzy sets is the of each element from two sets |
| A. | maximum |
| B. | minimum |
| C. | equal to |
| D. | not equal to |
| Answer» C. equal to | |
| 97. |
The a cut of a fuzzy set A is a crisp set defined by :- |
| A. | {x|ua(x)>a} |
| B. | {x|ua(x)>=a} |
| C. | {x|ua(x)<a} |
| D. | {x|ua(x)<=a} |
| Answer» C. {x|ua(x)<a} | |
| 98. |
A Fuzzy rule can have |
| A. | multiple part of ante |
| B. | only single part of |
| C. | multiple part of ant |
| D. | only single part of ante |
| Answer» D. only single part of ante | |
| 99. |
Which of the following is/are type of fuzzy interference method |
| A. | mamdani |
| B. | sugeno |
| C. | rivest |
| D. | only a and b |
| Answer» E. | |
| 100. |
Which of the folloowing is not defuzzifier method |
| A. | centroid of area |
| B. | mean of maximu |
| C. | largest of maximum |
| D. | hypotenuse of triangle |
| Answer» E. | |